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Bayesian inference / Hierarchical Bayes model / Frequentist inference / Graphical model / Prior probability / Statistics / Bayesian statistics / Bayesian network


Dispersal in a hurry: Bayesian learning from surveillance to establish area freedom from plant pests with early dispersal
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Document Date: 2013-01-16 00:51:01

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File Size: 826,84 KB

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City

Canberra / Cambridge / Perth / London / /

Company

Oxford University Press / Bayesian Networks / Complex Surveillance Systems / New Zealand Journal / Surveillance Reference Group / /

Country

Australia / United Kingdom / /

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Facility

Queensland University of Technology / /

IndustryTerm

search strategy / closed form solution / telephone conference / low technology approach / search effort / /

Organization

International Congress / Consultative Committee for Emergency Plant Pests / Cooperative Research Centre for National Plant Biosecurity / eNSW Department of Primary Industries / Queensland University of Technology / Brisbane / Australian Government Publishing Service / Australian Centre of Excellence for Risk Analysis / MRC Biostatistics Unit / Oxford University / /

Person

Gardner / D. Lunn / Spiegelhalter / Andrew Robinson / Chris Andersone / Susie / Myrtle Rust / Barry / Terry Walshe / Lindsay Penrosed / Nichole Hammondc / John Kean / Johnson / N. G. Best / Hester / A. Thomas / Martin / Cindy Hauser / Sharyn Taylorf / /

Position

D. J. / inspector / /

Product

WinBUGS version 1.4.3 / simulated using WinBUGS version 1.4.3 / WinBUGS 1.4.3 / /

ProvinceOrState

Western Australia / /

PublishedMedium

Psychological Review / New Zealand Journal of Ecology / /

Region

Western Australia / /

Technology

t-1 / Simulation / /

URL

http /

SocialTag